Volunteer Summary

Table

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.37) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.18 (95% CI [18.53, 19.83], t(130) = 57.79, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.63, 95% CI [-0.30, 1.56], t(130) = 1.33, p = 0.184; Std. beta = 0.30, 95% CI [-0.14, 0.75])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.11, 0.46], t(130) = -0.80, p = 0.423; Std. beta = -0.15, 95% CI [-0.53, 0.22])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.05, 95% CI [-1.11, 1.21], t(130) = 0.09, p = 0.928; Std. beta = 0.03, 95% CI [-0.53, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.55) and the part related to the fixed effects alone (marginal R2) is of 7.41e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.03 (95% CI [10.50, 11.55], t(130) = 41.13, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.48, 1.02], t(130) = 0.71, p = 0.480; Std. beta = 0.16, 95% CI [-0.29, 0.62])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.28, 0.79], t(130) = 0.93, p = 0.353; Std. beta = 0.15, 95% CI [-0.17, 0.47])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-0.92, 0.66], t(130) = -0.33, p = 0.743; Std. beta = -0.08, 95% CI [-0.55, 0.40])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.26 (95% CI [43.03, 45.48], t(130) = 70.61, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.85, 95% CI [-0.91, 2.61], t(130) = 0.95, p = 0.343; Std. beta = 0.22, 95% CI [-0.23, 0.67])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.94, 1.03], t(130) = 0.09, p = 0.931; Std. beta = 0.01, 95% CI [-0.24, 0.26])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.39, 95% CI [-1.07, 1.85], t(130) = 0.52, p = 0.602; Std. beta = 0.10, 95% CI [-0.28, 0.48])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 8.03e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.62 (95% CI [14.96, 16.27], t(130) = 46.59, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.02, 0.87], t(130) = -0.16, p = 0.876; Std. beta = -0.04, 95% CI [-0.49, 0.42])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.44, 0.82], t(130) = 0.59, p = 0.555; Std. beta = 0.09, 95% CI [-0.21, 0.40])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.32, 95% CI [-0.62, 1.25], t(130) = 0.67, p = 0.504; Std. beta = 0.15, 95% CI [-0.30, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.33 (95% CI [11.89, 12.78], t(130) = 54.57, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-0.75, 0.52], t(130) = -0.36, p = 0.718; Std. beta = -0.08, 95% CI [-0.54, 0.37])
• The effect of time point [2nd] is statistically significant and negative (beta = -0.52, 95% CI [-0.89, -0.15], t(130) = -2.78, p = 0.005; Std. beta = -0.38, 95% CI [-0.64, -0.11])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.54, 95% CI [-0.01, 1.09], t(130) = 1.92, p = 0.055; Std. beta = 0.39, 95% CI [-7.67e-03, 0.78])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.45) and the part related to the fixed effects alone (marginal R2) is of 7.72e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.33 (95% CI [10.88, 11.78], t(130) = 49.29, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.63, 0.66], t(130) = 0.05, p = 0.956; Std. beta = 0.01, 95% CI [-0.44, 0.47])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-0.66, 0.35], t(130) = -0.60, p = 0.547; Std. beta = -0.11, 95% CI [-0.46, 0.25])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.36, 95% CI [-0.38, 1.11], t(130) = 0.96, p = 0.338; Std. beta = 0.26, 95% CI [-0.27, 0.78])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.48) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.41 (95% CI [42.99, 45.83], t(130) = 61.22, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.08, 95% CI [-0.96, 3.11], t(130) = 1.04, p = 0.301; Std. beta = 0.24, 95% CI [-0.21, 0.68])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -1.29, 95% CI [-2.87, 0.28], t(130) = -1.61, p = 0.108; Std. beta = -0.28, 95% CI [-0.63, 0.06])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-2.30, 2.36], t(130) = 0.02, p = 0.981; Std. beta = 6.09e-03, 95% CI [-0.50, 0.52])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.51 (95% CI [24.21, 28.82], t(130) = 22.56, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -2.35, 95% CI [-5.65, 0.95], t(130) = -1.40, p = 0.163; Std. beta = -0.32, 95% CI [-0.76, 0.13])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 1.16, 95% CI [-1.07, 3.38], t(130) = 1.02, p = 0.308; Std. beta = 0.16, 95% CI [-0.14, 0.46])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.16, 95% CI [-4.46, 2.13], t(130) = -0.69, p = 0.489; Std. beta = -0.16, 95% CI [-0.60, 0.29])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 45.10 (95% CI [41.67, 48.53], t(130) = 25.77, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -3.43, 95% CI [-8.34, 1.49], t(130) = -1.37, p = 0.172; Std. beta = -0.31, 95% CI [-0.75, 0.13])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 2.46, 95% CI [-0.77, 5.70], t(130) = 1.49, p = 0.136; Std. beta = 0.22, 95% CI [-0.07, 0.52])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.22, 95% CI [-6.01, 3.58], t(130) = -0.50, p = 0.619; Std. beta = -0.11, 95% CI [-0.54, 0.32])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.82 (95% CI [19.67, 21.97], t(130) = 35.49, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.96, 95% CI [-0.68, 2.61], t(130) = 1.15, p = 0.252; Std. beta = 0.27, 95% CI [-0.19, 0.73])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-1.18, 1.23], t(130) = 0.04, p = 0.966; Std. beta = 7.29e-03, 95% CI [-0.33, 0.34])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.41, 95% CI [-2.20, 1.37], t(130) = -0.46, p = 0.648; Std. beta = -0.12, 95% CI [-0.61, 0.38])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.21 (95% CI [12.31, 14.10], t(130) = 28.81, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.79, 1.79], t(130) = 0.76, p = 0.449; Std. beta = 0.18, 95% CI [-0.28, 0.64])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-1.19, 0.56], t(130) = -0.71, p = 0.480; Std. beta = -0.11, 95% CI [-0.43, 0.20])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.80, 1.79], t(130) = 0.75, p = 0.452; Std. beta = 0.18, 95% CI [-0.29, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 9.23e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.54 (95% CI [19.83, 21.25], t(130) = 56.50, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-1.15, 0.89], t(130) = -0.26, p = 0.798; Std. beta = -0.06, 95% CI [-0.51, 0.40])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.70, 0.74], t(130) = 0.05, p = 0.956; Std. beta = 8.91e-03, 95% CI [-0.31, 0.33])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.90, 1.21], t(130) = 0.29, p = 0.774; Std. beta = 0.07, 95% CI [-0.40, 0.54])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.30) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.46 (95% CI [4.16, 4.76], t(130) = 29.07, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.40, 95% CI [-0.03, 0.83], t(130) = 1.83, p = 0.067; Std. beta = 0.41, 95% CI [-0.03, 0.86])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.21, 0.56], t(130) = 0.90, p = 0.371; Std. beta = 0.18, 95% CI [-0.22, 0.58])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.54, 0.60], t(130) = 0.09, p = 0.928; Std. beta = 0.03, 95% CI [-0.56, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.54) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.03 (95% CI [57.29, 60.76], t(130) = 66.71, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.73, 95% CI [-0.75, 4.22], t(130) = 1.37, p = 0.172; Std. beta = 0.32, 95% CI [-0.14, 0.78])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.91, 1.70], t(130) = -0.11, p = 0.911; Std. beta = -0.02, 95% CI [-0.35, 0.32])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.23, 95% CI [-2.44, 2.90], t(130) = 0.17, p = 0.865; Std. beta = 0.04, 95% CI [-0.45, 0.54])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 9.72e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.64 (95% CI [15.07, 16.21], t(130) = 53.44, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.18, 95% CI [-1.00, 0.64], t(130) = -0.43, p = 0.665; Std. beta = -0.10, 95% CI [-0.56, 0.35])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-0.92, 0.31], t(130) = -0.98, p = 0.327; Std. beta = -0.17, 95% CI [-0.51, 0.17])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.69, 95% CI [-0.22, 1.59], t(130) = 1.48, p = 0.138; Std. beta = 0.38, 95% CI [-0.12, 0.88])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 3.13e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.44 (95% CI [11.98, 12.89], t(130) = 53.59, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.19, 95% CI [-0.84, 0.46], t(130) = -0.58, p = 0.562; Std. beta = -0.13, 95% CI [-0.59, 0.32])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.45, 0.42], t(130) = -0.08, p = 0.939; Std. beta = -0.01, 95% CI [-0.31, 0.29])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.46, 0.83], t(130) = 0.57, p = 0.572; Std. beta = 0.13, 95% CI [-0.32, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 5.27e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.08 (95% CI [27.12, 29.04], t(130) = 57.44, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.37, 95% CI [-1.75, 1.00], t(130) = -0.53, p = 0.593; Std. beta = -0.12, 95% CI [-0.58, 0.33])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.29, 95% CI [-1.20, 0.63], t(130) = -0.61, p = 0.542; Std. beta = -0.09, 95% CI [-0.40, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.86, 95% CI [-0.50, 2.22], t(130) = 1.24, p = 0.213; Std. beta = 0.29, 95% CI [-0.16, 0.74])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 1.43e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.95 (95% CI [13.58, 16.31], t(130) = 21.48, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.21, 95% CI [-1.74, 2.17], t(130) = 0.21, p = 0.831; Std. beta = 0.05, 95% CI [-0.41, 0.50])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.23, 95% CI [-1.35, 0.88], t(130) = -0.41, p = 0.683; Std. beta = -0.05, 95% CI [-0.31, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.73, 1.58], t(130) = -0.08, p = 0.932; Std. beta = -0.02, 95% CI [-0.40, 0.37])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 5.57e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.72 (95% CI [2.62, 4.81], t(130) = 6.66, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.53, 95% CI [-2.10, 1.04], t(130) = -0.66, p = 0.509; Std. beta = -0.15, 95% CI [-0.60, 0.30])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.73, 0.78], t(130) = 0.06, p = 0.956; Std. beta = 6.10e-03, 95% CI [-0.21, 0.22])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.10, 1.15], t(130) = 0.04, p = 0.967; Std. beta = 6.67e-03, 95% CI [-0.31, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 3.40e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.28 (95% CI [2.28, 4.28], t(130) = 6.42, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.34, 95% CI [-1.77, 1.10], t(130) = -0.46, p = 0.646; Std. beta = -0.11, 95% CI [-0.56, 0.35])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.66, 1.00], t(130) = 0.39, p = 0.695; Std. beta = 0.05, 95% CI [-0.21, 0.31])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-1.08, 1.39], t(130) = 0.25, p = 0.806; Std. beta = 0.05, 95% CI [-0.34, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 9.53e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.43 (95% CI [49.06, 53.80], t(130) = 42.58, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.71, 95% CI [-5.10, 1.69], t(130) = -0.99, p = 0.325; Std. beta = -0.23, 95% CI [-0.68, 0.22])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.54, 95% CI [-2.30, 1.22], t(130) = -0.60, p = 0.547; Std. beta = -0.07, 95% CI [-0.30, 0.16])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 2.38, 95% CI [-0.23, 4.99], t(130) = 1.79, p = 0.074; Std. beta = 0.32, 95% CI [-0.03, 0.66])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 3.81e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.39 (95% CI [47.73, 53.05], t(130) = 37.11, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.13, 95% CI [-2.68, 4.95], t(130) = 0.58, p = 0.561; Std. beta = 0.14, 95% CI [-0.32, 0.60])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.18, 95% CI [-2.64, 2.28], t(130) = -0.14, p = 0.887; Std. beta = -0.02, 95% CI [-0.32, 0.28])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.78, 95% CI [-4.42, 2.87], t(130) = -0.42, p = 0.677; Std. beta = -0.09, 95% CI [-0.54, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Table